Meriden, KS
Meriden, KS's wildfire risk, in USFS's own numbers
Out of every US place USFS scores, Meriden lands at the 68th percentile for wildfire risk to structures — well above the national norm for wildfire risk — a figure built from its 457 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Meriden at the 69th percentile, close to its 68th-percentile risk score.
Where Meriden's buildings actually sit
79.2% of Meriden's 457 buildings fall in USFS's Indirect exposure zone — ember cast rather than direct flame — against 20.6% Direct and 0.2% Minimal. Vent screens and roofing material matter more here than lot clearing alone.
Where Meriden ranks
Meriden scores 68th nationally and 64th within Kansas — close enough that its state context doesn't change the picture the national number already gives. Among the 31,521 US communities USFS scores, Meriden ranks 10,210 for wildfire risk (1 is highest) and 18,125 by building count (1 is largest). Within Kansas alone, it ranks 263 of 721 places by risk. See the full county-by-county picture for Kansas on its state page.
What this risk score means for insurance
At the 68th percentile nationally, Meriden carries the high rating that has pushed some carriers to limit new business in similarly-scored places elsewhere in the country. Worth comparing quotes rather than assuming last year's renewal terms still apply.
Hardening a home in Meriden
Meriden's 79.2% Indirect-exposure share points at embers, not flame contact, as the main pathway — ember-resistant vents and non-combustible roofing rank ahead of defensible space here. Detail in the home-hardening guide.
Where Meriden's figures come from
Every one of the two percentiles behind Meriden's 10,210-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Meriden's dominant indirect exposure actually means, with real examples from across the dataset.